Drug repositioning based on gene expression data for human HER2-positive breast cancer

Abstract

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer represents approximately 15–30% of all invasive breast cancers. Despite the recent advances in therapeutic practices of HER2 subtype, drug resistance and tumor recurrence still have remained as major problems. Drug discovery is a long and difficult process, so the aim of this study is to find potential new application for existing therapeutic agents. Gene expression data for breast invasive carcinoma were retrieved from The Cancer Genome Atlas (TCGA) database. The normal and tumor samples were analyzed using Linear Models for Microarray Data (LIMMA) R package in order to find the differentially expressed genes (DEGs). These genes were used as entry for the library of integrated network-based cellular signatures (LINCS) L1000CDS2 software and suggested 24 repurposed drugs. According to the obtained results, some of these drugs including vorinostat, mocetinostat, alvocidib, CGP-60474, BMS-387032, AT-7519, and curcumin have significant functional similarity and structural correlation with FDA-approved breast cancer drugs. Based on the drug-target network, which consisted of the repurposed drugs and their target genes, the aforementioned drugs had the highest degrees. Moreover, the experimental approach verified curcumin as an effective therapeutic agent for HER2 positive breast cancer. Hence, our work suggested that some repurposed drugs based on gene expression data can be noticed as potential drugs for the treatment of HER2-positive breast cancer.